AI Automation & Business Analysis
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Key skills for this role
About the Role
FAB is seeking a Manager for AI Automation & Business Analysis to bridge business teams and DAAI by translating operational needs into requirements and rapidly prototyping AI automations.
Key Skills for This Role
Responsibilities
- Rapidly build small scale AI automations, prototypes, and proof of concept solutions using Microsoft Copilot Studio, Claude code, Appian, prompt driven workflows, and other approved enterprise tools
- Design and refine prompts, agent instructions, workflow logic, validation checks, and human in the loop controls to improve solution reliability and business usability
- Partner with GCOO business teams to identify, assess, and prioritize lightweight AI automation opportunities that improve productivity, turnaround time, control, and service quality
- Translate business problems into clear use cases, process maps, user stories, acceptance criteria, data needs, risks, and delivery ready requirements for DAAI and technology teams
- Bridge business stakeholders, DAAI specialists, platform teams, risk, compliance, and operations teams to accelerate use case discovery, readiness, and delivery alignment
- Manage the GCOO AI automation backlog, including intake, triage, impact assessment, prioritization, dependency tracking, status reporting, and escalation of delivery risks
- Assess solution feasibility, expected benefits, operational readiness, data availability, information security considerations, and responsible AI implications before progressing use cases
- Support adoption by preparing guidance, demos, stakeholder communications, operating procedures, and handover material for business users and support teams
- Monitor delivered automations for usage, effectiveness, issues, feedback, and opportunities for continuous improvement or scale up through formal DAAI delivery channels
Requirements
- Bachelor's degree in Business, Computer Science, Information Technology, Engineering, Data Analytics, or related discipline
- 2 3 years of hands on experience with Microsoft Copilot Studio, Claude code, Appian, workflow automation, low code/no code platforms, or similar enterprise automation tools
- Working knowledge of generative AI, agentic AI concepts, prompt engineering, retrieval based solutions, human in the loop review, and AI assisted business workflows
- Ability to rapidly prototype practical automations, test outputs, refine prompts/workflows, document limitations, and convert learnings into scalable delivery requirements
- 5–10 years of experience across business analysis, process automation, digital transformation, technology delivery, product ownership, or AI enabled operations
- Strong business analysis skills including stakeholder engagement, process discovery, requirements elicitation, user story writing, acceptance criteria definition, and benefits articulation
- Good understanding of data handling, access controls, auditability, operational risk, information security, and responsible AI considerations in a regulated banking environment
- Strong communication skills with ability to explain AI enabled solutions, trade offs, risks, and business value to both technical and non technical stakeholders
- Experience working in Agile delivery environments and managing small backlogs, prioritization forums, demos, and iterative delivery cycles is preferred
Full Job Posting
Group Function and Role Purpose
- FAB is a leading financial institution committed to responsible innovation, operational excellence, and practical adoption of AI.
- The Client Servicing Engineering function acts as a center of excellence within the GCOO office.
- The Manager, AI Automation & Business Analysis will bridge business teams and DAAI by translating operational needs into clear requirements and rapidly prototyping lightweight AI automations.
Key Responsibilities
- Rapidly build small scale AI automations, prototypes, and proof of concept solutions using Microsoft Copilot Studio, Claude code, Appian, prompt driven workflows, and other approved enterprise tools.
- Design and refine prompts, agent instructions, workflow logic, validation checks, and human in the loop controls.
- Partner with GCOO business teams to identify, assess, and prioritize lightweight AI automation opportunities.
- Translate business problems into clear use cases, process maps, user stories, acceptance criteria, data needs, risks, and delivery ready requirements.
- Bridge business stakeholders, DAAI specialists, platform teams, risk, compliance, and operations teams.
- Manage the GCOO AI automation backlog, including intake, triage, impact assessment, prioritization, dependency tracking, status reporting, and escalation.
- Assess solution feasibility, expected benefits, operational readiness, data availability, information security considerations, and responsible AI implications.
- Support adoption by preparing guidance, demos, stakeholder communications, operating procedures, and handover material.
- Monitor delivered automations for usage, effectiveness, issues, feedback, and opportunities for continuous improvement.
Required Skills and Qualifications
- Bachelor's degree in Business, Computer Science, Information Technology, Engineering, Data Analytics, or a related discipline.
- 2 3 years of hands on experience with Microsoft Copilot Studio, Claude code, Appian, workflow automation, low code/no code platforms, or similar enterprise automation tools.
- Working knowledge of generative AI, agentic AI concepts, prompt engineering, retrieval based solutions, human in the loop review, and AI assisted business workflows.
- Ability to rapidly prototype practical automations, test outputs, refine prompts/workflows, document limitations, and convert learnings into scalable delivery requirements.
- 5–10 years of experience across business analysis, process automation, digital transformation, technology delivery, product ownership, or AI enabled operations.
- Strong business analysis skills, including stakeholder engagement, process discovery, requirements elicitation, user story writing, acceptance criteria definition, and benefits articulation.
- Good understanding of data handling, access controls, auditability, operational risk, information security, and responsible AI considerations in a regulated banking environment.
- Strong communication skills with the ability to explain AI enabled solutions, trade offs, risks, and business value to both technical and non technical stakeholders.
- Experience working in Agile delivery environments and managing small backlogs, prioritization forums, demos, and iterative delivery cycles is preferred.
Attributes
- Change Advocate and Delivery Accelerator: Identifies high value opportunities for AI enabled improvement, challenges manual ways of working, and helps teams adopt practical automation.
- Analytical and Innovation Mindset: Connects business needs, process pain points, AI capabilities, data constraints, and governance requirements to shape pragmatic solutions.
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